class_docstr: Atari 2600 preprocessing wrapper.
  
  This class follows the guidelines in Machado et al. (2018),
  "Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents".
  
  Specifically, the following preprocess stages applies to the atari environment:
  - Noop Reset: Obtains the initial state by taking a random number of no-ops on reset, default max 30 no-ops.
  - Frame skipping: The number of frames skipped between steps, 4 by default
  - Max-pooling: Pools over the most recent two observations from the frame skips
  - Termination signal when a life is lost: When the agent losses a life during the environment, then the environment is terminated.
      Turned off by default. Not recommended by Machado et al. (2018).
  - Resize to a square image: Resizes the atari environment original observation shape from 210x180 to 84x84 by default
  - Grayscale observation: If the observation is colour or greyscale, by default, greyscale.
  - Scale observation: If to scale the observation between [0, 1) or [0, 255), by default, not scaled.
docstr: Resets the environment using preprocessing.
docstr_tok: ["Resets","the","environment","using","preprocessing","."]
code: def reset(self, **kwargs):
      """Resets the environment using preprocessing."""
      # NoopReset
      _, reset_info = self.env.reset(**kwargs)
  
      noops = (
          self.env.unwrapped.np_random.integers(1, self.noop_max + 1)
          if self.noop_max > 0
          else 0
      )
      for _ in range(noops):
          _, _, terminated, truncated, step_info = self.env.step(0)
          reset_info.update(step_info)
          if terminated or truncated:
              _, reset_info = self.env.reset(**kwargs)
  
      self.lives = self.ale.lives()
      if self.grayscale_obs:
          self.ale.getScreenGrayscale(self.obs_buffer[0])
      else:
          self.ale.getScreenRGB(self.obs_buffer[0])
      self.obs_buffer[1].fill(0)
  
      return self._get_obs(), reset_info
  
file_path: gym/gym/wrappers/atari_preprocessing.py
imports: import numpy
  import gym
  from gym.spaces import Box
label_desc: Use image node_id 4 for calling the AtariPreprocessing obj's underlying member method code with example usage: obj.reset() and returns: self,  reset_info